IRC Seminar, presented by Dr Bin Wu: "Three important dimensions in development of complex data visual analysis"

Abstract:

Information management and data mining are widely used in the analysis and decision-making process in various industries. Compared with traditional data analysis methods based on mathematical logic, visual data mining draws and visually presents data based on visual cognitive rules, uses visual cognitive channels to enhance the user's understanding of data, and helps users extract regular pattern hidden in complex data. This report combines actual cases to introduce how to design visual layout drawing algorithms, data analysis interaction modes, visual cognitive evaluation scales and other elements based on the characteristics of data samples, so as to effectively improve the efficiency of data mining and provide more effective data analysis solutions for various industries.

Bio:

Dr Wu Bin is from the School of Art of Henan University of Science and Technology in China. He is the director of the Animation Department of the School of Art, an associate professor, and a graduate tutor. He has won the titles of Henan Province Teaching Model, Luoyang City Outstanding Teacher, and Henan Province Outstanding Young Social Science Expert.

Dr Bin mainly engages in research in the field of digital media art, and has a comprehensive academic research background that integrates art and information engineering (mainly computer graphics). He has presided over and participated in more than 20 research projects, including "Research on Visual Analysis Methods of Ecological Economic Data", "Prototype Analysis and Reconstruction of User Interaction Behaviour in Mobile Game Design", and "Research on Information Architecture Optimization Strategy for Digital Product Display".

He has published more than 30 papers, including "Force-directed Segmented Skeleton Binding Drawing of Clustered Data in Parallel Coordinates", "Evaluation Method of Binding Drawing of Clustered Data in Parallel Coordinates", "Visual Analysis of Directed Weighted Network Data Based on Force-directed Algorithm Optimization", and "Learning Performance Evaluation Based on Visual Clustering Analysis of Teaching Data". In recent years, he has gradually formed his own research topics in the fields of visual design, computer science, information management and data analysis. He focuses on the design, optimization, application and evaluation of visual style drawing algorithms in the process of complex data visual analysis, and cooperates with experts from multiple industries to carry out research on visual data mining applications.